To develop and externally validate a prediction model for major bleeding in patients with a TIA or ischemic stroke on antiplatelet agents.
We combined individual patient data from 6 randomized clinical trials (CAPRIE, ESPS-2, MATCH, CHARISMA, ESPRIT, and PRoFESS) investigating antiplatelet therapy after TIA or ischemic stroke. Cox regression analyses stratified by trial were performed to study the association between predictors and major bleeding. A risk prediction model was derived and validated in the PERFORM trial. Performance was assessed with the c statistic and calibration plots.
Major bleeding occurred in 1,530 of the 43,112 patients during 94,833 person-years of follow-up. The observed 3-year risk of major bleeding was 4.6% (95% confidence interval [CI] 4.4%-4.9%). Predictors were male sex, smoking, type of antiplatelet agents (aspirin-clopidogrel), outcome on modified Rankin Scale ≥3, prior stroke, high blood pressure, lower body mass index, elderly, Asian ethnicity, and diabetes (S2TOP-BLEED). The S2TOP-BLEED score had a c statistic of 0.63 (95% CI 0.60-0.64) and showed good calibration in the development data. Major bleeding risk ranged from 2% in patients aged 45-54 years without additional risk factors to more than 10% in patients aged 75-84 years with multiple risk factors. In external validation, the model had a c statistic of 0.61 (95% CI 0.59-0.63) and slightly underestimated major bleeding risk.
The S2TOP-BLEED score can be used to estimate 3-year major bleeding risk in patients with a TIA or ischemic stroke who use antiplatelet agents, based on readily available characteristics. The discriminatory performance may be improved by identifying stronger predictors of major bleeding.
Pharmacology, Toxicology and Pharmaceutical Science
5
6%
Unspecified
3
3%
Biochemistry, Genetics and Molecular Biology
2
2%
Other
12
14%
Unknown
31
35%
Attention Score in Context
Attention Score in Context
This research output has an Altmetric Attention Score of 159. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 April 2019.
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#315,465
of 32,797,349 outputs
Outputs from Neurology
#742
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Outputs of similar age
#5,254
of 348,217 outputs
Outputs of similar age from Neurology
#15
of 335 outputs
Altmetric has tracked 32,797,349 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
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We're also able to compare this research output to 335 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.
